val expected =
      """
      |--AaB03x
      |Content-Disposition: form-data; name="submit-name"
      |
      |Larry
      |--AaB03x
      |Content-Disposition: form-data; name="files"
      |Content-Type: multipart/mixed; boundary=BbC04y
      |
      |--BbC04y
      |Content-Disposition: file; filename="file1.txt"
      |Content-Type: text/plain; charset=utf-8
      |

          result.add(story)
          i++
        }
      } finally {
        storyInputStream.close()
      }
    }

    if (result.isEmpty()) {
      // missing files
      result.add(Story.MISSING)
    }

    return result
  }

## `File` 임포트

`fastapi` 에서 `File` 과 `UploadFile` 을 임포트 합니다:

```Python hl_lines="1"
{!../../../docs_src/request_files/tutorial001.py!}
```

## `File` 매개변수 정의

`Body` 및 `Form` 과 동일한 방식으로 파일의 매개변수를 생성합니다:

```Python hl_lines="7"
{!../../../docs_src/request_files/tutorial001.py!}
```

!!! info "정보"
    `File` 은 `Form` 으로부터 직접 상속된 클래스입니다.

    artifactRules = """
        *.psoutput => $hiddenArtifactDestination
        *.threaddump => $hiddenArtifactDestination
        build/report-* => $hiddenArtifactDestination
        build/tmp/teŝt files/** => $hiddenArtifactDestination/teŝt-files
        build/errorLogs/** => $hiddenArtifactDestination/errorLogs
        subprojects/internal-build-reports/build/reports/incubation/all-incubating.html => incubation-reports

install_deps()

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

1. Config serving (XDS)

### Config Ingestion

Istio reads from over 20 different resources types, and aggregates them together to build the proxy configuration. These resources can be sourced from Kubernetes (via watches), files, or over xDS; Kubernetes is by far the most common usage, though.

Primarily for historical reasons, ingestion is split into a few components.

#### ConfigStore

for an example.

See
[this commit](https://github.com/tensorflow/tensorflow/commit/5f7f05a80aac9b01325a78ec3fcff0dbedb1cc23)
as a rough example of the steps below.

All the files referenced below are located in the same directory as this README,
unless indicated otherwise.

1) Add the new version to the `VERSIONS` variable inside
   `tensorflow/tools/toolchains/python/python_repo.bzl`. \

## Configure Prometheus to use AlertManager

Add below section to your `prometheus.yml`
```yaml
alerting:
  alertmanagers:
  - static_configs:
    - targets: ['localhost:9093']
rule_files:
  - rules.yml
```
Here `rules.yml` is the file which should contain the alerting rules defined.

## Add rules for your deployment

    description = "Download all dependencies to the Gradle cache"
    doLast {
      for (configuration in configurations) {
        if (configuration.isCanBeResolved) {
          configuration.files
        }
      }
    }
  }

  normalization {
    runtimeClasspath {
      metaInf {
        ignoreAttribute("Bnd-LastModified")
      }
    }
  }
}

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